Market Data Explained

Market Data Explained
Author: Marc Alvarez
Publisher: Elsevier
Total Pages: 136
Release: 2011-04-01
Genre: Business & Economics
ISBN: 0080465781

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Market Data Explained is intended to provide a guide to the universe of data content produced by the global capital markets on a daily basis. Commonly referred to as “market data , the universe of content is very wide and the type of information correspondingly diverse. Jargon and acronyms are very common. As a result, users of marker data typically face difficulty in applying the content in analysis and business applications. This guide provides an independent framework for understanding this diversity and streamlining the process of referring to content and how it relates to today’s business environment. The book achieves this goal by providing a consistent frame of reference for users of market data. As such, it is built around the concept of a data model – a single, coherent view of the capital markets independent of any one source, such as an exchange. In particular it delineates clearly between the actual data content and how it is delivered (i.e., realtime data streams versus reference data). It shows how the data relates across the universe of securities (i.e., stocks, bonds, derivatives etc.). In this way it provides a logical framework for understanding how new content can be added over time as the business develops. Special features: 1. Uniqueness – this is the first comprehensive catalog and taxonomy to be made available for a business audience 2. Industry Acceptance – the framework described in this book is implemented as a relational data model in the industry today and used by blue chip multinational firms 3. Comprehensiveness – there are no arbitrary distinctions made based on asset class or data type (the legacy approach). The model presented in this book is fully cross asset and makes no distinction between data types (i.e., realtime versus historical/reference data) or sources 4. Independence – the framework is an independent, objective overview of how the data content integrates to provide a coherent view of the data produced by the global capital markets on a daily and intra-day basis. It provides a logical framework for referring to the content and entities that are so intrinsic to this industry First and only single, comprehensive desk reference to market data produced by the global capital markets on a daily basis Provides a comprehensive catalog of the market data and a common structure for navigating the complex content and interrelationships Provides a common taxonomy and naming conventions that handles the highly varied, geographically and language dependent nature of the content

Market Data Explained

Market Data Explained
Author: Marc Alvarez
Publisher:
Total Pages: 0
Release: 2006
Genre: Capital market
ISBN:

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This book is intended to provide a guide to the universe of data content produced by the global capital markets on a daily basis. Commonly referred to as "market data?, the universe of content is very wide and the type of information correspondingly diverse. Jargon and acronyms are very common. As a result, users of marker data typically face difficulty in applying the content in analysis and business applications. This guide provides an independent framework for understanding this diversity and streamlining the process of referring to content and how it relates to today's business environment. The book achieves this goal by providing a consistent frame of reference for users of market data. As such, it is built around the concept of a data model - a single, coherent view of the capital markets independent of any one source, such as an exchange. In particular it delineates clearly between the actual data content and how it is delivered (i.e., realtime data streams versus reference data). It shows how the data relates across the universe of securities (i.e., stocks, bonds, derivatives etc.). In this way it provides a logical framework for understanding how new content can be added over time as the business develops. Special features: 1. Uniqueness - this is the first comprehensive catalog and taxonomy to be made available for a business audience 2. Industry Acceptance - the framework described in this book is implemented as a relational data model in the industry today and used by blue chip multinational firms 3. Comprehensiveness - there are no arbitrary distinctions made based on asset class or data type (the legacy approach). The model presented in this book is fully cross asset and makes no distinction between data types (i.e., realtime versus historical/reference data) or sources 4. Independence - the framework is an independent, objective overview of how the data content integrates to provide a coherent view of the data produced by the global capital markets on a daily and intra-day basis. It provides a logical framework for referring to the content and entities that are so intrinsic to this industry *First and only single, comprehensive desk reference to market data produced by the global capital markets on a daily basis *Provides a comprehensive catalog of the market data and a common structure for navigating the complex content and interrelationships *Provides a common taxonomy and naming conventions that handles the highly varied, g...

Technical Analysis of the Financial Markets

Technical Analysis of the Financial Markets
Author: John J. Murphy
Publisher: Penguin
Total Pages: 576
Release: 1999-01-01
Genre: Business & Economics
ISBN: 110165919X

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John J. Murphy has now updated his landmark bestseller Technical Analysis of the Futures Markets, to include all of the financial markets. This outstanding reference has already taught thousands of traders the concepts of technical analysis and their application in the futures and stock markets. Covering the latest developments in computer technology, technical tools, and indicators, the second edition features new material on candlestick charting, intermarket relationships, stocks and stock rotation, plus state-of-the-art examples and figures. From how to read charts to understanding indicators and the crucial role technical analysis plays in investing, readers gain a thorough and accessible overview of the field of technical analysis, with a special emphasis on futures markets. Revised and expanded for the demands of today's financial world, this book is essential reading for anyone interested in tracking and analyzing market behavior.

High-frequency data analysis

High-frequency data analysis
Author: Nadine Hirte
Publisher: GRIN Verlag
Total Pages: 30
Release: 2004-06-23
Genre: Mathematics
ISBN: 3638285227

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Seminar paper from the year 2003 in the subject Mathematics - Statistics, grade: 2.0 (B), European University Viadrina Frankfurt (Oder), language: English, abstract: Today the financial market becomes more complex and includes more competition. Reasons are trends like globalization, liberalization and lower-cost trading mechanism. The market microstructure research has the aim of an efficient market. It is focused on the structure of the financial market. The investigation becomes possible through the availability of high- frequency data. Those data exist especially in the United States and like that most of the research focuses this market. To explain the phenomena, which have been found adequate, models that fit the characteristics of high- frequency data have to be developed. The research is important to understand actions on the market as well as develop new efficient mechanism. One part of the market microstructure field is the bid-ask spread. It will be focus of this paper. In the first two parts it will be discussed theoretically. In the last part one model will be empirically analyzed and tested on its usefulness and validity. The second part of this paper explains the basic elements surrounding the research of bid-ask spread. Those are the financial market, market microstructure as well as high-frequency data. In the following part the bid-ask spread itself, approaches, researches and models focussing the spread will be discussed. The model of Roll (1984) will be explained in detail. The last part will be the empirical analysis of the model of Roll. It is analyzed with data from the NASDAQ.

Applied Quantitative Finance

Applied Quantitative Finance
Author: Mauricio Garita
Publisher: Springer Nature
Total Pages: 240
Release: 2021-09-03
Genre: Business & Economics
ISBN: 3030291413

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This book provides both conceptual knowledge of quantitative finance and a hands-on approach to using Python. It begins with a description of concepts prior to the application of Python with the purpose of understanding how to compute and interpret results. This book offers practical applications in the field of finance concerning Python, a language that is more and more relevant in the financial arena due to big data. This will lead to a better understanding of finance as it gives a descriptive process for students, academics and practitioners.

Stock price analysis through Statistical and Data Science tools: An Overview

Stock price analysis through Statistical and Data Science tools: An Overview
Author: Vinaitheerthan Renganathan
Publisher: Vinaitheerthan Renganathan
Total Pages: 107
Release: 2021-04-30
Genre: Business & Economics
ISBN: 9354579736

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Stock price analysis involves different methods such as fundamental analysis and technical analysis which is based on data related to price movement of the stock in the past. Price of the stock is affected by various factors such as company’s performance, current status of economy and political factor. These factors play an important role in supply and demand of the stock which makes the price to be volatile in the short term. Investors and stock traders aim to book profit through buying and selling the stocks. There are different statistical and data science tools are being used to predict the stock price. Data Science and Statistical tools assume only the stock price’s historical data in predicting the future stock price. Statistical tools include measures such as Graph and Charts which depicts the general trend and time series tools such as Auto Regressive Integrated Moving Averages (ARIMA) and regression analysis. Data Science tools include models like Decision Tree, Support Vector Machine (SVM), Artificial Neural Network (ANN) and Long Term and Short Term Memory (LSTM) Models. Current methods include carrying out sentiment analysis of tweets, comments and other social media discussion to extract the hidden sentiment expressed by the users which indicate the positive or negative sentiment towards the stock price and the company. The book provides an overview of the analyzing and predicting stock price movements using statistical and data science tools using R open source software with hypothetical stock data sets. It provides a short introduction to R software to enable the user to understand analysis part in the later part. The book will not go into details of suggesting when to purchase a stock or what at price. The tools presented in the book can be used as a guiding tool in decision making while buying or selling the stock. Vinaitheerthan Renganathan www.vinaitheerthan.com/book.php

The Work of Wall Street

The Work of Wall Street
Author: Sereno Stansbury Pratt
Publisher:
Total Pages: 322
Release: 1908
Genre: Securities industry
ISBN:

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High-frequency Financial Market Data

High-frequency Financial Market Data
Author: Owain Ap Gwilym
Publisher:
Total Pages: 162
Release: 1999
Genre: Capital market
ISBN: 9781899332496

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A consideration of the sources, management, manipulation and uses of high-frequency financial market data. It applies HFD to model development for data analysis, trading, forecasting and risk management. Future trends are covered, and there is a bibliography of the literature.

Day Trading

Day Trading
Author: Justin Kuepper
Publisher: Tycho Press
Total Pages: 0
Release: 2015-04-10
Genre: Business & Economics
ISBN: 9781623155742

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All You'll Ever Need to Trade from Home When most people hear the term "day trader," they imagine the stock market floor packed with people yelling 'Buy' and 'Sell' - or someone who went for broke and ended up just that. These days, investing isn't just for the brilliant or the desperate—it's a smart and necessary move to ensure financial wellbeing. To the newcomer, day trading can be a confusing process: where do you begin, and how can you approach trading in a careful yet effective way? With Day Trading you'll get the basics, then: Learn the Truth About Trading Understand The Psychology of Trading Master Charting and Pattern-recognition Study Trading Options Establish Trading Strategies & Money Management Day Trading will let you make the most out of the free market from the comfort of your own computer.

MARKET MODELS: A GUIDE TO FINANCIAL DATA ANALYSIS (With CD )

MARKET MODELS: A GUIDE TO FINANCIAL DATA ANALYSIS (With CD )
Author: Carol Alexander
Publisher:
Total Pages: 516
Release: 2009-01-01
Genre:
ISBN: 9788126523702

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Market_Desc: Primarily this book has been written for financial institutions (investment banks, asset management companies, investment analysis personnel, corporate treasuries, insurance companies, pension funds, risk management companies/consultants and regulatory bodies.) Special Features: "The author uses an applications-based approach."Includes the latest developments in VaR. About The Book: Models play a crucial role in today's financial markets and an understanding and appreciation of how to model financial data is key to any finance practitioner's skill set. Model developers are faced with many decisions, about the data, methodology, model specification and testing, prior to the final model implementation. This is costly and how many media reports in recent years have highlighted the mismanagement of such resources! It is crucial to make the right choices at every stage of model development. But this is as much an 'art' as a 'science'. The talented interpretation of results is just as critical for success as the mathematical foundation. This new book is the first of its kind. As well as providing numerous real world examples to illustrate concepts in an accessible manner, the accompanying CD will allow the reader to implement the examples themselves and adapt them for their own purposes. Professor Carol Alexander, Chair of Risk Management at the ISMA Centre and one of the best known names in financial data analysis, provides an authoritative and up-to-date treatment of model development. She brings many new insights to the practicalities of volatility and correlation analysis, modelling the market risk of portfolios and statistical models. New models that are based on cointegration, principal component analysis, normal mixture densities, GARCH and many other areas are elegantly and rigorously explained, with an emphasis on concepts that makes this text accessible to a very wide audience. The book is also designed to be self contained, with many technical appendices. Market Models is the ideal reference for all those involved in model selection and development